def resolve_attempts(self, graphene_info, **kwargs):
limit = kwargs.get('limit')
results = get_schedule_attempt_filenames(graphene_info, self._schedule.name)
if limit is None:
limit = len(results)
latest_results = heapq.nlargest(limit, results, key=os.path.getctime)
attempts = []
for result_path in latest_results:
with open(result_path, 'r') as f:
line = f.readline()
if not line:
continue # File is empty
start_scheduled_execution_response = json.loads(line)
run = None
if 'errors' in start_scheduled_execution_response:
status = DauphinScheduleAttemptStatus.ERROR
json_result = start_scheduled_execution_response['errors']
else:
json_result = start_scheduled_execution_response['data'][
'startScheduledExecution'
]
typename = json_result['__typename']
if (
typename == 'StartPipelineExecutionSuccess'
or typename == 'LaunchPipelineExecutionSuccess'
):
status = DauphinScheduleAttemptStatus.SUCCESS
run_id = json_result['run']['runId']
run = graphene_info.schema.type_named('PipelineRun')(
graphene_info.context.instance.get_run_by_id(run_id)
)
elif typename == 'ScheduleExecutionBlocked':
status = DauphinScheduleAttemptStatus.SKIPPED
else:
status = DauphinScheduleAttemptStatus.ERROR
attempts.append(
graphene_info.schema.type_named('ScheduleAttempt')(
time=os.path.getctime(result_path),
json_result=json.dumps(json_result),
status=status,
run=run,
)
)
return attempts
def resolve_attempts_count(self, graphene_info):
attempt_files = get_schedule_attempt_filenames(graphene_info, self._schedule.name)
return len(attempt_files)